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Pattern Recognition & Machine Learning by Christopher M Bishop-- Hardcover
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Located in: Great Lakes, Illinois, United States
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eBay item number:156194253954
Item specifics
- Condition
- Pages
- 778
- Publication Date
- 2006-08-17
- Book Title
- Pattern Recognition and Machine Learning
- ISBN
- 9780387310732
- Subject Area
- Computers, Psychology, Mathematics
- Publication Name
- Pattern Recognition and Machine Learning
- Item Length
- 9.3 in
- Publisher
- Springer New York
- Subject
- Probability & Statistics / General, Intelligence (Ai) & Semantics, Cognitive Psychology & Cognition, Computer Vision & Pattern Recognition
- Series
- Information Science and Statistics Ser.
- Publication Year
- 2011
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 0.7 in
- Item Width
- 7 in
- Item Weight
- 75.7 Oz
- Number of Pages
- Xx, 778 Pages
About this product
Product Information
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same ?eld, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation pro- gation. Similarly, new models based on kernels have had signi'cant impact on both algorithms and applications. This new textbook re'ects these recent developments while providing a comp- hensive introduction to the ?elds of pattern recognition and machine learning. It is aimed at advanced undergraduates or ?rst year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or - chine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not - sential as the book includes a self-contained introduction to basic probability theory.
Product Identifiers
Publisher
Springer New York
ISBN-10
0387310738
ISBN-13
9780387310732
eBay Product ID (ePID)
51822478
Product Key Features
Publication Name
Pattern Recognition and Machine Learning
Format
Hardcover
Language
English
Subject
Probability & Statistics / General, Intelligence (Ai) & Semantics, Cognitive Psychology & Cognition, Computer Vision & Pattern Recognition
Series
Information Science and Statistics Ser.
Publication Year
2011
Type
Textbook
Subject Area
Computers, Psychology, Mathematics
Number of Pages
Xx, 778 Pages
Dimensions
Item Length
9.3 in
Item Height
0.7 in
Item Width
7 in
Item Weight
75.7 Oz
Additional Product Features
LCCN
2006-922522
Intended Audience
Scholarly & Professional
Number of Volumes
1 Vol.
Lc Classification Number
Q337.5
Reviews
"This beautifully produced book is intended for advanced undergraduates, PhD students, and researchers and practitioners, primarily in the machine learning or allied areas...A strong feature is the use of geometric illustration and intuition...This is an impressive and interesting book that might form the basis of several advanced statistics courses. It would be a good choice for a reading group." John Maindonald for the Journal of Statistical Software, From the reviews: "This beautifully produced book is intended for advanced undergraduates, PhD students, and researchers and practitioners, primarily in the machine learning or allied areas...A strong feature is the use of geometric illustration and intuition...This is an impressive and interesting book that might form the basis of several advanced statistics courses. It would be a good choice for a reading group." John Maindonald for the Journal of Statistical Software "In this book, aimed at senior undergraduates or beginning graduate students, Bishop provides an authoritative presentation of many of the statistical techniques that have come to be considered part of ?pattern recognition? or ?machine learning?'. ? This book will serve as an excellent reference. ? With its coherent viewpoint, accurate and extensive coverage, and generally good explanations, Bishop?'s book is a useful introduction ? and a valuable reference for the principle techniques used in these fields." (Radford M. Neal, Technometrics, Vol. 49 (3), August, 2007)
Table of Content
Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
Copyright Date
2006
Dewey Decimal
006.4
Dewey Edition
22
Illustrated
Yes
Item description from the seller
Seller assumes all responsibility for this listing.
eBay item number:156194253954
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Item location:
Great Lakes, Illinois, United States
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